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This study examines how ineffective Generative AI (GenAI) adoption in higher education can constrain scalable, high-quality practice and feedback in cybersecurity education. While prior work highlights GenAI’s educational benefits, portability, instructor adoptability, and governance-aligned deployment remain underexplored in assessment-adjacent contexts. We introduce GenAITS, a modular agentic tutoring workflow that operationalises mastery-oriented practice and rubric-aligned formative feedback through inspectable question-context-rubric bundles and instructor-controlled release gates. We evaluated GenAITS via an in-situ pre/post deployment across two postgraduate cybersecurity subjects (n = 52 paired responses), combining learner perception measures with educator reflections. Post-deployment ratings shifted directionally upward across engagement, perceived knowledge retention, resilience/retention, and transferability, consistent with improved perceived support for practice-and-feedback cycles rather than objective performance evidence.

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A Governable GenAI Tutoring Framework for Cybersecurity Education

  • 会议论文

  • 发表日期：

    2026年

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  • Madhav Mukherjee,
  • John Le,
  • Yang-Wai Chow

摘要

This study examines how ineffective Generative AI (GenAI) adoption in higher education can constrain scalable, high-quality practice and feedback in cybersecurity education. While prior work highlights GenAI’s educational benefits, portability, instructor adoptability, and governance-aligned deployment remain underexplored in assessment-adjacent contexts. We introduce GenAITS, a modular agentic tutoring workflow that operationalises mastery-oriented practice and rubric-aligned formative feedback through inspectable question-context-rubric bundles and instructor-controlled release gates. We evaluated GenAITS via an in-situ pre/post deployment across two postgraduate cybersecurity subjects (n = 52 paired responses), combining learner perception measures with educator reflections. Post-deployment ratings shifted directionally upward across engagement, perceived knowledge retention, resilience/retention, and transferability, consistent with improved perceived support for practice-and-feedback cycles rather than objective performance evidence.